Smart Vision Architecture Non-Uniform Pixel Parameter Control
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Solution Overview
Problem
Conventional cameras face challenges in achieving optimal resolution, dynamic range, and frame rate in local image regions due to high data rates and resource constraints, leading to inefficient use of bandwidth, memory, and power consumption.
Innovation Solution
The system employs a smart vision architecture with distributed image sensors and AI-driven pixel parameter control, allowing for non-uniform adjustment of pixel parameters across an image frame based on contextual understanding and saliency detection, optimizing parameters in regions with salient items while reducing them in non-salient regions to manage bandwidth, memory, and power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high performance parameters are applied across the entire frame to achieve required resolution, dynamic range and frame rate, then image quality is improved, but data rate becomes very high and unmanageable
Solution Approach 1:
The image frame is divided into multiple regions of interest (ROIs) based on semantic scene understanding. Different pixel parameters are applied to different regions, allowing high performance parameters to be concentrated only where needed (salient regions) rather than uniformly applied across the entire frame, thereby reducing overall data rate while maintaining image quality in critical areas.
Solution Approach 2:
The patent implements non-uniform pixel parameter control where each region of interest receives customized parameter settings based on its importance and content characteristics. Salient regions receive higher resolution, dynamic range, and frame rate parameters, while non-salient regions use reduced parameters, optimizing the trade-off between image quality and data rate.
2Manufacturing precision
If high performance parameters are applied across the entire frame, then image quality is improved, but power consumption increases
Solution Approach 1:
The frame is segmented into regions requiring different performance levels. By activating high performance parameters only in salient regions and using reduced parameters in non-salient regions, the system significantly reduces overall power consumption while maintaining image quality where it matters most.
Solution Approach 2:
Different power consumption levels are allocated to different regions based on their importance. Critical regions receive sufficient power for high-quality capture, while non-critical regions operate at lower power levels, optimizing the balance between image quality and power consumption.
3Manufacturing precision
If high performance parameters are applied across the entire frame, then image quality is improved, but memory storage requirements increase
Solution Approach 1:
By segmenting the frame into regions of varying importance and applying different compression and storage parameters to each region, the system reduces total memory storage requirements while preserving image quality in salient regions where it is most needed.
4Manufacturing precision
If high performance parameters are applied across the entire frame, then image quality is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary semantic scene understanding and saliency detection to identify regions of interest before capturing the image. This pre-processing step enables the subsequent application of optimized pixel parameters to specific regions, simplifying the overall system architecture by replacing uniform high-performance parameters with targeted, region-specific parameter control.
Data Source
AI summary
Modules and control units cooperate to simultaneously and independently control and adjust pixel parameters non-uniformly at regional increments across an entire image captured in an image frame by pixels in a pixel array. Pixel parameter changes for pixels in a given region occur, based on i) a contextual understanding of what contextually was happening in the one or more prior image frames and ii) whether salient items are located within that region. Additionally, guidance is sent to the sensor control unit to i) increase or decrease pixel parameters within those regions with salient items and then either to i) maintain, ii) increase or iii) decrease pixel parameters within regions without salient items in order to stay within any i) bandwidth limitations ii) memory storage, and/or iii) power consumptions limitations imposed by 1) one or more image sensors or 2) the communication loop between the sensor control unit and the image processing unit.